Systems and methods for analyzing facial expressions, identifying intent and transforming images through review of facial expressions

ABSTRACT

Methods of analyzing a plurality of facial expressions are disclosed that include: identifying a subject person, utilizing the subject person to create an image of a known target, removing at least one distracter expression from the target image to form a revised target image, and reviewing the revised target image with at least one third party participant to form a final target image. Additional methods of analyzing a plurality of facial expressions include: identifying a subject person, utilizing the subject person to create an image of a known target, digitizing the target image, removing at least one distracter expression from the target image to transform the target image to a revised target image, and reviewing the revised target image with at least one third party participant to transform the revised target image to a final target image. Software for implementing contemplated methods include: a set speed function, a pre-test phase function, an instruction phase function, a practice phase function, and a post-test phase function.

This United States Utility Application claims priority to U.S.Provisional Application Ser. No. 61/203,592 filed on Dec. 24, 2008,which is commonly owned and incorporated herein in its entirety.

FIELD OF THE SUBJECT MATTER

The field of the subject matter relates generally to systems and methodsfor identifying the intent of an individual through facial expressions,and more particularly to systems and methods for identifying deadly ordangerous intent through facial expressions before a premeditated orloss of impulse control assault.

BACKGROUND

Reading people well, building rapport, deducing information andeliciting response are crucial skills in today's society for anyone whointeracts with the public. Interactive training is the most effectiveway to improve this skill set. Studies show that there is a highagreement about the specific nature of facial expressions that arevisible in the moments before either a premeditated physical assault, oran assault due to a momentary loss of impulse control. It has also beennoted that premeditated and impulsive assault expressions are verydifferent.

While it is understood that facial expressions may vary with the intentof an individual, there are no conventional methods, systems or softwareto quantify or qualify exactly what these expressions are or how anindividual may be able identify facial expressions. Contemplatedembodiments provide novel systems and methods to create facialexpression images and automate technology to scan for the presence offacial expressions associated with violent and dangerous behavior, andin particular those facial expressions associated with deadly intent.Such systems and methods therefore provide a few seconds warning tothose in heightened danger. Furthermore, contemplated embodiments alsoprovide novel systems and methods to train those in harms way to bealerted to deadly intent facial expressions to scan for the presence ofdeadly intent.

SUMMARY

Methods of analyzing a plurality of facial expressions are disclosedthat include: identifying a subject person, utilizing the subject personto create an image of a known target, removing at least one distracterexpression from the target image to form a revised target image, andreviewing the revised target image with at least one third partyparticipant to form a final target image.

Additional methods of analyzing a plurality of facial expressionsinclude: identifying a subject person, utilizing the subject person tocreate an image of a known target, digitizing the target image, removingat least one distracter expression from the target image to transformthe target image to a revised target image, and reviewing the revisedtarget image with at least one third party participant to transform therevised target image to a final target image.

Software for implementing contemplated methods include: a set speedfunction, a pre-test phase function, an instruction phase function, apractice phase function, and a post-test phase function.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a contemplated screen shot for a contemplated embodimentwhere the outline of the tool is presented.

FIG. 2 shows a contemplated screen shot for a contemplated embodimentwhere the speed of the face displays can be set.

FIG. 3 shows a contemplated screen shot for a contemplated embodimentduring the PRE-TEST stage.

FIG. 4 shows a contemplated screen shot for a contemplated embodimentduring the INSTRUCTION stage.

FIG. 5 shows a contemplated screen shot for a contemplated embodimentduring the INSTRUCTION stage.

FIG. 6 shows a contemplated screen shot for a contemplated embodimentduring the PRACTICE stage.

FIG. 7 shows a contemplated screen shot for a contemplated embodimentduring the POST-TEST stage.

FIG. 8 shows a contemplated screen shot for a contemplated embodimentwhere the score is presented.

FIG. 9 is a block diagram illustrating a computer system in accordancewith a contemplated embodiment.

FIG. 10 is a block diagram of the remote server shown in FIG. 9.

FIG. 11 is a block diagram of the client computer shown in FIG. 9.

DETAILED DESCRIPTION

Methods of analyzing a plurality of facial expressions are disclosedthat include: identifying a subject person, utilizing the subject personto create an image of a known target, removing at least one distracterexpression from the target image to form a revised target image, andreviewing the revised target image with at least one third partyparticipant to form a final target image. Additional methods ofanalyzing a plurality of facial expressions include: identifying asubject person, utilizing the subject person to create an image of aknown target, digitizing the target image, removing at least onedistracter expression from the target image to transform the targetimage to a revised target image, and reviewing the revised target imagewith at least one third party participant to transform the revisedtarget image to a final target image. Software for implementingcontemplated methods include: a set speed function, a pre-test phasefunction, an instruction phase function, a practice phase function, anda post-test phase function.

Contemplated embodiments disclose systems and methods for identifyingdangerous intent based upon facial expressions. As will be appreciatedby one of skill in the art, contemplated systems and methods disclosedare equally applicable to the identification of facial expressionsdisclosing other characteristics and intent. Research shows thatspecific facial expressions are associated with an impending attack.While such expression are not an absolute certainty, there is reasonableprobability to associate certain facial expressions with specificphysically responses. The purpose of identifying a particular facialexpression with a particular intent is to alert an individual of theneed to be more attentive to the individual displaying the facialexpression. It may also alert the person to prepare to respond or take apreemptive action. While there is no certainty that any facialexpression will necessarily precede a dangerous action, the ability toidentify and be aware of such physical manifestations is beneficial.

In contemplated embodiments, images are created to display anger intentfacial expressions. This creation of images is unique from presentsystems where images are created and then individuals classify theimages. In contemplated embodiments, instead of showing a set of facesand asking people to pick the one they saw before a deadly assault, thetarget images are created by having people who have recently beenassaulted create the face they saw, converted into revised target imagesand then transformed into final target images. This novel approach is anoperative concept of contemplated embodiments because there is noabsolute certainty in the facial expressions that may appear. Thisactive creation step by contemplated users and third party participantsis particularly important when trying to characterize facial expressionsof people of varying cultures, such as a terrorist or extremist. Thesecontemplated methods are significant in that the contemplated systemsare relevant in worldwide applications. Furthermore, contemplatedembodiments may assist a traveling individual in being cognitive ofcultural differences.

The creation of dangerous intent facial expressions involves multiplesteps. First, an individual who has been attacked, saw the facialexpression of the attacker and can identify the expression isinterviewed in order to create the target image. Then the individual isshown alternate images to ensure “distracter expressions” are removedfrom the created image to form a revised target image. As used herein,the phrase “distracter expressions” is used to refer to thoseexpressions in alternate facial expression images that are notconsidered relevant or particularly helpful in identifying the dangerousintent.

Then, the created revised target image is shown to at least one thirdparty participant who has experience in dealing with individuals fromthe particular cultural group who have perpetrated the particular typeof attack. This created facial revised target image may be confirmedmultiple times by one or more third party participants. One reason forthe multiple confirmations is to ensure any cultural bias is removed.The images may also be shown to and confirmed by people within thecultural group from which the expression was created.

Once a final target image is created, the image may be used to analyzeand compare it to images obtained through other sources. Such analysismay be performed by scanning the created image and identifying keyfeatures as discussed below that depict dangerous intent. Theseidentified features are then compared with at least one image obtainedthrough other sources. Contemplated comparisons may be done manually,automatically or through a combination thereof, as will be describedherein.

In contemplated embodiments, facial expressions may be analyzed byevaluating the movement of facial muscles. In this novel approachspecific muscular groups are associated with particular intent. Theintensity, or amount of muscle movement, may effect the evaluation ofthe expression. Table 1 below shows a contemplated analysis.

TABLE 1 Facial Action Coding Expression System U Muscle name Intensitylevel Premeditated 4 Corrugator super- A-C Assault cilii, Depressorsupercilii 5 Levator palpebrae A-C superioris 7 Orbicularis oculi, A-Bpars palpebralis 23 Orbicularis oris Top and/or bottom; AC; may or maynot be present 17 Mentalis May or may not be present Loss of Control, 4Corrugator super- C-E version 1 cilii, Depressor supercilii 5 Levatorpalpebrae C-E superioris 7 Orbicularis oculi, A-B: may or may parspalpebralis not be present 23 Orbicularis oris Top and/or bottom; A-D 26Jaw drop Face reddening Loss of Control, 4 Corrugator super- D-E version2 cilii, Depressor supercilii 5 Levator palpebrae C-E superioris 7Orbicularis oculi, C-E pars palpebralis 9 Levator palpebrae C-Esuperioris 20 Risorius w/ C-E platysma Face reddening Jaw clench 10Levator palpebrae May or may not superioris be present 16 DepressorLabii May or may not inferioris be present 23 Orbicularis oris May ormay not be present 21 May or may not be present

While contemplated disclosed methods and systems may be utilized througha manual process, in most embodiments, an automated, or softwareapplication is contemplated. FIG. 9 is an exemplary depiction of onesuch system 900. FIG. 9 is a block diagram of a system 900 for analyzingfacial expressions via a network 920 from a remote device or clientcomputer 910, then transforming and delivering the results to the remotedevice 910. The systems comprise a remote server 920 linked to a network930. The network may be any suitable network, such as a Local AreaNetwork (LAN), Wide Area Network (WAN), an Extranet, an Internet or acombination thereof. However, in a contemplated embodiment, the network930 is the Internet. Although only one remote server is depicted, oneskilled in the art will recognize that any number of remote servers maybe utilized.

The network 930 is coupled to a client computer 910 through acommunication link 950, such as a wireless connection, phone line, cableline, digital subscriber line, infra-red link or the like. The clientcomputer 910 includes any computing device that can couple to thenetwork 930 via the communication line 950. The client computer 910 maybe a personal computer, laptop computer, handheld, computer, mainframecomputer, PDA, smartphone or the like, including a combination thereof.

FIG. 10 is a block diagram of the remote server 920 shown in FIG. 9. Theremote server 920 contains a plurality of components such as at leastone central processing unit (CPU) 710, communications circuitry 720, atleast one communication port 730, a memory 740 and at least one bus 870that connects the aforementioned components. The communicationscircuitry 720 and the communications port 730 preferably include one ormore Network Interface Cards (NICs) configured to communicate with thenetwork 930 and the client computer 910. The memory 740 preferablycomprises Random Access Memory (RAM) and/or Read Only Memory (ROM). Thememory 740 preferably includes an operating system 742 which hasinstructions for communicating, processing, accessing, storing, orsearching data. Examples of suitable operating systems include MICROSOFTWINDOWS™, DOS™, UNIX™, LINUX™ and MACOS™. In addition, memory 740preferably includes communication procedures 744, authenticationprocedures 746, a network server 748, content 750, an installationreference 752, installation procedures 754, installation files 756, auser database 758, one or more source directories 760 containingsoftware and/or other data.

The communications procedures 744 are used for communicating with boththe client computer 950 and the network 930. The authenticationprocedures 754, are used for authenticating users, such as through ausername and password system. Successful completion of theauthentication procedures gives users access to the installation files756 on the server 920.

The network server 748 receives and delivers data between itself and theclient computer 910. The network server 748 also executes server-sidescripts (CGI scripts, JSPs, ASPs, etc.) that provide functions such asdatabase searching. The content 750 is any information that is availablefor retrieval by the user, including Web-pages, images, music, audio,white papers, drivers, as well as training, educational and referencematerials. The content 750 is not presented in a programming languagebut rather in a “presentation language.” Examples of presentationlanguages include HTML, XML, XHTML and CGI.

The installation procedures 754 may be used to install fertilizerselection software onto the client computer 910.

FIG. 11 is a block diagram of client computer 910. Client computer 910comprises a plurality of components, such as a central processing unit(CPU) 810; communications circuitry 820; ports 830(1)-(N), where port 1is connected to network 650; input/output devices 832, such as a monitorand keyboard; a memory 840; and at least one bus 860 that connects theaforementioned components.

The memory 840 preferably includes an operating system 842, such asMICROSOFT WINDOWS™, DOS™, UNIX™, LINUX™ and MACOS™, which hasinstructions for communicating, processing, accessing, storing, andsearching data. The memory 842 further preferably includes:communications procedures 844, authentication procedures 846, a networkclient 848, and a cache 850 for temporarily storing data. In use, thecache may contain an interpreter 852, and client computer configurationdata 854.

Communications procedures 844 are used for communicating with thenetwork 930. Authentication procedures 846 are used to authenticate aclient computer's access to the remote server 920.

The network client 848 receives the content 750 from the remote server920. The network client 920 may be a browser or similar type program,such as MICROSOFT'S INTERNET EXPLORER™ or NETSCAPE'S NAVIGATOR™.

Interpreter 852 is a high-level programming language translator thattranslates a program statement into machine language, executes it, andthen proceeds to the next statement. In one embodiment, interpreter 852creates parameter tags to the applet tag in content 750.

Installation procedures 754 are used to download and install facialexpression intent software onto the client computer 910. The clientcomputer configuration data 854 contains the client computer'sconfiguration information, such as the hardware and software that makesup the client computer 910 (FIG. 9).

A user may access the training software by utilizing an automated systemsuch as a web based program that is accessible through a network, bydownloading software from a remote server to a client computer or byinstalling software from a disc, CD, DVD, or other storage media. Forexample, a user could access a web based program which would guide theuser through each of the contemplated facial analysis training modulesdescribed above in conjunction with FIGS. 1-8 or alternatively, the usercould download or install software on his local computer. Furthermore,the web-based or local based software could store answers, provideanalysis of the user's progress, and provide feedback.

Contemplated embodiments provide for multiple steps in implementing thesystem. FIG. 1 shows a screenshot of a contemplated embodiment where the“OUTLINE OF THE TOOL” 100 is presented to the user, wherein a set ofdescriptions 110 are presented to the user (not shown). The user maychoose to go “BACK” 120 to a previous screen (not shown) or “CONTINUE”130 to the next screen (not shown).

The user continues to the next screen, as shown in FIG. 2, to the “SETSPEED” screen shot 200. A set of instructions 210 is provided to theuser (not shown) in order to set the response speed. The user may chooseto go “BACK” 220 to a previous screen (not shown) or “CONTINUE” 230 tothe next screen (not shown).

The user then continues to the next screen, as shown in FIG. 3, to the“PRE-TEST” screen shot 300. A set of instructions 310 is provided to theuser (not shown). The user may choose to go “HOME” 320 (not shown) or“QUIT” 330. The pre-test analyzes the ability of a user to recognizefacial expressions with dangerous intent prior to beginning a trainingmodule.

During the pre-test phase, the user is presented with multiple targetimages, whether they are revised target images or final target images,depicting a facial expression. The images provided include images ofdangerous intent and non-dangerous intent. Each image is displayed for aspecified period of time, for example one second. The user is then givena predetermined period of time to respond as described below. During thepredetermined period of time, the user must decide whether or not thefacial expression depicts a dangerous intent facial expression. The usermust then select the appropriate response button. If the user fails torespond, the response is considered an incorrect response. The totalnumber or correct and incorrect responses is tracked and the results arethen displayed for the user. The results may be displayed merely innumerical format, alternatively percentages may be provided. In acontemplated embodiment, the user is shown twenty facial expressionsduring the PRE-TEST stage, however, this number is not intended to be alimitation on the scope and one of skill in the art will appreciate thatthe number of facial expressions depicted may be greater or less.Alternatively, the images may be displayed upon initiation by the userfor example through the use of the click of a button or depression of akey.

After the pre-test, the user is provided with instructions foridentifying dangerous intent facial expression during the “INSTRUCTION”stage, as shown in FIGS. 4 and 5. These two Figures both show screenshots (400 and 500, respectively) of the “INSTRUCTION” stage, where theuser (not shown) is able to review various instructions (410 and 510,respectively), along with representative images (420 and 520,respectively). The user may choose to go “HOME” 430 and 530 (not shown)or “QUIT” 440 or 540.

The instructions include the depiction of dangerous intent facialexpressions and contrast the dangerous intent facial expressiondepictions with depiction of distracter facial expressions (facialexpressions displaying intent or emotion other than dangerous intent).During the instruction phase, the images provided include images ofdangerous intent and non-dangerous intent. This novel tool could also beused for example, by a person planning a trip where the user may beshown images from the cultural region the user will be visiting in orderto help the user be more aware of cultural differences in expressions.

Next, a practice phase is provided which allows a user to practicehoning his facial expression tools based upon the knowledge gainedduring the instruction portion described immediately above. Acontemplated “PRACTICE” phase is depicted in FIG. 6, where a screen shot600 of the “PRACTICE” phase is shown. A set of instructions 610 isprovided to the user (not shown). The user may choose to go “HOME” 620(not shown) or “QUIT” 630.

During the practice phase, the user is presented an image depicting afacial expression. The image is displayed for one second, or any otherpredetermined period of time. After the image is displayed, the usermakes a selection deciding whether the image displayed depicts adangerous intent expression or not by selecting the appropriateresponse. No time limit is set for the user to respond or optionally, atime limit may be preset or selected by the user. If an incorrectselection is made, the image is redisplayed. The image may be displayedautomatically or the user may select to view the image again byselecting an appropriate button. In a contemplated embodiment, thepractice phase includes forty images, however, this number is notintended to be a limitation on the scope and one of skill in the artwill appreciate that the number of facial expressions depicted may begreater or less. In addition, in another embodiment of the practicephase a neutral expression is morphed into a dangerous intent facialexpression to assist the user in identifying changes in facialexpression that occur.

Finally, a post-test is provided which examines the users' improvedability to recognize dangerous intent facial expressions through thepractice or instruction module. A contemplated “POST-TEST” phase isdepicted in FIG. 7, where a screen shot 700 of the “POST-TEST” phase isshown. A set of instructions 710 is provided to the user (not shown).The user may choose to go “HOME” 720 (not shown) or “QUIT” 730. Duringthe post-test, images of facial expressions are displayed for one secondor any other predetermined period of time. The user is given a set timeto respond to the image and select whether or not the image displayed isone of dangerous intent. If the user fails to respond, the response isconsidered an incorrect response.

The total number or correct and incorrect responses is tracked and theresults are then displayed for the user. A contemplated “YOUR SCORE”phase is depicted in FIG. 8, where a screen shot 800 of the “YOUR SCORE”phase is shown. A Pre-Test Accuracy Score 805 and a Post-Test AccuracyScore 815 is provided to the user (not shown). The user may choose to go“BACK” 820 (not shown) or “QUIT” 830. The user (not shown) may alsodecide to save the score data by filling out the input blocks provided850. The results may be displayed merely in numerical format,alternatively percentages may be provided. In a contemplated embodiment,the user is shown twenty facial expressions during the post-testhowever, this number is not intended to be a limitation on the scope ofthe invention and one of skill in the art will appreciate that thenumber of facial expressions depicted may be greater or less.

The results of the pre-test and post-test are provided to the user andmay also be provided to an administrator or other trainer. The resultsmay be provided in tabular format, by percentages, or any otherstatistically relevant means. The results are compared and provided tothe user to allow the user to see his improvement and also to providefeedback to the administrator on the effectiveness of the training tool.

In working with different facial expressions, it is important tounderstand what might lead to a determination that a particular facialexpression is neutral, angry or threatening. A neutral expression is theexpression displayed by an individual showing very little emotion. Afacial expression depicting only hints of anger may include a tighteningof the lips but no other obvious signs of anger. A target image, whetherit is a revised target image or final target image as contemplatedherein, depicting an angry expression may involve the lowering of thebrows, raising of the upper eyelid, tightening of the lip and pushing upof the lower lip. A target image, whether it is a revised target imageor final target image as contemplated herein, displaying a contemplatedpremeditated assault facial expression may be displayed by an individualwho has planned an attack and is carefully carrying out the plan orplanning to carry it out. This premeditated assault facial expression ischaracterized by a lowering of the brows, raising of the upper eyelidthat produces a staring quality and a tightening of the lips. The lowerlip may be pushed up, as if the attacker is trying to control hisemotions in carrying out the planned attacked. This facial expression isa controlled expression of anger that displays the look of determinationand concentration.

A target image, whether it is a revised target image or final targetimage as contemplated herein, displaying an exemplar loss of impulsecontrol facial expression may be seen on an individual who has just losthis temper and is about to attack. The facial expression ischaracterized by a slight lowering of the brows, strong raising of theupper eyelid that produces bulging, staring quality to the eyes, astrong tightening of the lips and a distinct absence of the pushing upof the lower lip. The absence of the lower lip push may be significantbecause it is usually associated with emotion control and in theexpression the individual has lost control of his anger.

A, whether it is a revised target image or final target image ascontemplated herein, target image of a facial expression displayedduring an attack is similar to the loss of impulse control but is muchmore intense. Such an expression may include a displaying of the teeth,squinted eyes in addition to the characteristic described above inrelation to the loss of impulse control facial expression.

The above facial expression and image descriptions are not intended tobe an exhaustive representation of dangerous intent facial expressionsbut are only exemplar in nature. Angry facial expressions are oftenconfused with expression of disgust and contempt. Facial expressions ofdisgust and contempt may include such characteristics as nose wrinkling,raising of the upper lip, and changes in skin tone. Contempt is usuallybut not always associated with unilateral or asymmetrical expression.These expressions are very different from angry expressions associatedwith premeditated assault of loss of impulse control and contemplatedembodiments are designed to enable a user to distinguish between thedifferent types of expression.

The system and method described are designed to operate at varyingspeeds to improve the recognition time of the user. The response time toseeing a facial expression, analyzing it and responding may be set by anadministrator, alternatively the user may select the response time. Forexample, the response time may be set so that the user must respondwithin 1 second after seeing the facial expression or it may be expandedto any length of time deemed appropriate for training. In one embodimentthe response time is automatically reduced as the user's proficiencyincreases.

While the above embodiments are described with respect to target imagesdisplaying facial expressions of dangerous intent, one of skill in theart will appreciate that the embodiments not limited to dangerous intentfacial expressions and other facial expressions and the evaluationthereof are contemplated within the scope of this disclosure.

In conjunction with the novel method, another novel method fordeveloping target images is disclosed. In this approach, the DWISanalysis is performed as follows. A specified number of participantswere selected. From the participants, cases, to be included in theimagery, are selected based on whether the participant had witnessed orexperienced a physical assault or been threatened with an assault. Acontrol group is also selected from those participants who answered noto never seeing the facial expression of someone just before they made aphysical assault, no to not remembering someone's expression before anassault, and no to seeing someone's expression but not seeing it in thea group of pictures displayed.

Analyses were performed on the selected sample participants' responsesso that a total of one point was assigned to each subset for eachparticipant: Loss of Control (LC), and Premeditated Assault (PA). Thedata is then statistically evaluated using various methods. For example,chi-squares, one way analysis of variance, percentage and mean data,percentage and mean data to run Spearman's rhos.

From the results the top four photographs are identified and examined.Examples of the analysis and detail of such are included in the Examplessection.

EXAMPLES Example 1 1.0 DIWS Analysis—Merged Data

Original sample had n of 585. From Israel there were 199 participants,from UK there were 50 participants, from Scotland Yard there were 84participants, from Canada there were 68 participants, and from Koreathere were 184 participants. Dropped all Scotland Yard data.

From remaining data, selected cases based on whether the participant hadwitnessed or experienced a physical assault. For Israel and Korea, aparticipant was selected if he or she had said yes to experiencing orwitnessing an assault on or off duty. For UK, a participant was selectedif he or she had said yes to being threatened with physical assault,being assaulted, or witnessing an assault. For Canada, a participant wasselected if he or she answered no to never seeing the facial expressionof someone just before they made a physical assault, no to notremembering someone's expression before an assault, and no to seeingsomeone's expression but not seeing it in the 12 pictures.

Selected sample had n of 385. From Israel there were 161 participants,from UK there were 46 participants, from Canada there were 46participants, and from Korea there were 132 participants. All analyseswere performed on this selected sample.

Transformed data so that a total of one point was assigned to eachsubset for each participant: Loss of Control (LC), and PremeditatedAssault (PA).

Ran 24 chi-squares with country as the IV and photograph chosen as theDV. For LC, significant results for photos 4, 6, 7, 10, and 11. (SeeTable 2). For PA, significant results for photos 4, 5, 10 and 12. (SeeTable 8).

Ran 24 one-way ANOVAS with country as IV and transformed data as the DV.For LC, significant results for photos 4, 6, 7, and 10. (See Table 3).For PA, significant results for photos 5, 10, and 12. (See Table 9).

Used percentage and mean data to run Spearman's rhos between countriesfor LC. For percentage data, significant among all country pairs. Formeans data, significant for all country pairs except for Korea andCanada. (See Table 4). Used percentage and mean data to run Spearman'srhos between countries for PA. For percentage data, significant for allcountry pairs except for Korea and UK. For means data, significant forall country pairs except for Korea and UK, and Korea and Canada. (SeeTable 10).

Identified top four photos chosen for LC (See Table 5) and PA (See Table11) for percent chosen and means by country.

Examined top four photographs chosen for LC (See Tables 6 and 7) and PA(See Tables 12 and 13) by looking at all possible pairs. Data weretransformed so that participants were given one point for choosingeither of the photos in a pair, and zero points for not. Additionally,for the data in which one point was given for each subset, all possiblepairs from top four were summed.

TABLE 2 Percent chosen for each photo by country for loss of control(LC); Chi-square analyses for country on percent chosen for each photo.Across Israel UK BC Korea Countries Chi-Squares Photo % for Ranking %for Ranking % for Ranking % for Ranking % for Ranking Asymp. Sig. Id LCfor LC LC for LC LC for LC LC for LC LC for LC x² df (2 sided) 1 3.1 90.0 10 4.7 6 3.0 10 2.9 11 1.89 3 .60 2 63.8 2 67.4 1 48.8 2 70.5 1 64.82 6.87 3. 08 3 4.4 7 2.2 7 4.7 6 5.3 8 4.5 7 .79 3 .85 4 5.0 5 4.3 6 4.76 15.9 5 8.7 5 13.43 3 .00 5 3.8 8 0.0 10 0.0 11 6.8 7 3.9 8 6.56 3 .096 79.4 1 67.4 1 51.2 1 66.7 2 70.3 1 14.89 3 .00 7 3.1 9 2.2 7 11.6 52.3 12 3.7 9 8.85 3 .03 8 40.6 4 34.8 4 27.9 3 34.1 4 36.2 4 2.93 3 .409 2.5 12 2.2 7 4.7 6 4.5 9 3.4 10 1.33 3 .40 10 5.0 5 15.2 5 0.0 11 13.66 8.7 6 13.42 3 .00 11 49.4 3 50.0 3 23.3 4 58.3 3 49.6 3 15.97 3 .00 123.1 9 0.0 10 4.7 6 3.0 10 2.9 11 1.89 3 .60

TABLE 3 Means for each photo by country for loss of control Percentchosen for each photo by country for loss of control (LC); Chi-squareanalyses for country on percent chosen for each photo. Across Israel UKBC Korea Countries Photo Means Ranking Means Ranking Means Ranking MeansRanking Means Ranking ANOVA Id for LC for LC for LC for LC for LC for LCfor LC for LC for LC for LC F df Sig. η_(p) ² 1 .0103 12 .0000 10 0.2916 .0094 11 .0109 12 1.30 3 .28 .01 2 .2451 2 .3111 1 .2835 2 .2545 1.2607 2 1.00 3 .39 .01 3 .0144 9 .0054 7 .0279 7 .0201 8 .0168 7 .61 3.61 .01 4 .0176 6 .0435 6 .0123 8 .0541 5 .0328 5 2.98 3 .03 .02 5 .012410 .0000 11 .0000 11 .22226 7 .0130 9 2.21 3 .09 .02 6 .3083 1 .2893 2.2912 1 .2255 2 .2754 1 3.36 3 .02 .03 7 .0145 8 .0030 8 .0519 5 .007612 .0149 8 2.96 3 .03 .02 8 .1404 4 .1157 4 .1149 4 .1233 4 .1286 4 .413 .75 .00 9 .0104 11 .0030 9 .0123 8 .0151 9 .0113 11 .44 3 .73 .00 10.0207 5 .0526 5 .0000 11 .0453 6 .0307 6 3.15 3 .03 .02 11 .1829 3 .17373 .1170 3 .2073 3 .1828 3 2.03 3 .11 .02 12 .0156 7 .0000 12 .0123 8.0107 10 .0116 10 .250 3 .68 .00

TABLE 4 Spearman's rho between countries for loss of control for percentchosen and means. Percent Means chosen Israel UK Canada Korea Israel.88* .61* .94* UK .89* .72* .87* Canada .61* .66* .54* Korea .85* .89*.49 *p < .05

TABLE 5 Top four photographs for loss of control for percent chosen andmeans by country Country Percent chosen Means Israel 6, 2, 11, 8 6, 2,11, 8 UK 2 = 6, 11, 8 2, 6, 11, 8 Canada 6, 2, 8, 11 6, 2, 11, 8 Korea2, 6, 11, 8 2, 6, 11, 8 Across Countries 6, 2, 8, 11 6, 2, 11, 8

TABLE 6 Percentages for photographs chosen for loss of control on alldata 6 2 11 8 6 + 2 6 + 11 6 + 8 2 + 11 2 + 8 11 + 8 Israel 79.4 63.849.4 40.6 90.0 86.3 87.5 81.9 80.6 77.5 UK 67.4 67.4 50.0 34.8 89.1 78.369.6 82.6 73.9 65.2 BC 51.2 48.8 23.3 27.9 74.4 62.8 55.8 58.1 60.5 41.9Korea 66.7 70.5 58.3 34.1 83.3 84.1 85.6 89.4 85.6 78.8

TABLE 7 Means for photographs chosen for loss of control on all data 6 211 8 6 + 2 6 + 11 6 + 8 2 + 11 2 + 8 11 + 8 Israel 0.3083 0.2451 0.18290.1404 0.5534 0.4913 0.4488 0.4281 0.3856 0.3234 UK 0.2893 0.3111 0.17370.1157 0.6004 0.4630 0.4050 0.4848 0.4267 0.2893 BC 0.2912 0.2835 0.11700.1149 0.5747 0.4081 0.4060 0.4005 0.3984 0.2319 Korea 0.2255 0.25450.2073 0.1233 0.4800 0.4327 0.3487 0.4618 0.3778 0.3305

TABLE 8 Percent chosen for each photo by country for premeditatedassault (PA); Chi-square analyses for country on percent chosen for eachphoto Across Israel UK BC Korea Countries Chi-Squares Photo % forRanking % for Ranking % for Ranking % for Ranking % for Ranking Asymp.Sig. Id PA for PA PA for PA PA for PA PA for PA PA for PA x² df (2sided) 1 27.5 4 15.6 8 16.3 5 21.2 5 22.6 5 4.60 3 .20 2 3.1 12 4.4 124.7 11 6.1 12 4.5 12 1.46 3 .69 3 40.6 2 28.9 2 27.9 2 36.4 3 36.3 23.67 3 .30 4 56.9 1 26.7 3 51.2 1 56.8 1 52.6 1 14.29 3 .00 5 30.0 317.8 6 14.0 7 41.7 2 30.8 3 16.67 3 .00 6 6.9 11 11.1 9 11.6 8 6.8 117.9 11 1.90 3 .59 7 16.3 7 17.8 6 9.3 9 13.6 7 14.7 7 1.76 3 .62 8 12.58 24.4 4 7.0 10 12.9 10 13.4 8 6.39 3 .09 9 24.0 5 20.0 5 16.3 5 28.8 424.5 4 3.38 3 .34 10 7.5 10 6.7 11 2.3 12 16.7 6 10.0 10 11.00 3 .01 1110.6 9 11.1 9 20.9 3 13.6 7 12.9 9 3.40 3 .33 12 22.5 35.6 1 20.9 3 13.67 20.8 6 10.34 3 .02

TABLE 9 Means for each photo by country for premeditated assault (PA);One-way ANOVAs for country on each photo Across Israel UK BC KoreaCountries Photo Means Ranking Means Ranking Means Ranking Means RankingMeans Ranking ANOVA Id for PA for PA for PA for PA for PA for PA for PAfor PA for PA for PA F df Sig. η_(p) ² 1 .1014 4 .0533 9 .0735 5 .0766 5.0839 5 1.24 3 .29 .01 2 .0135 12 .0258 11 .0077 11 .0252 11 .0183 12.59 3 .62 .01 3 .1604 2 .1311 3 .1216 2 .1296 3.= .1418 2 .71 3 .55 .014 .2246 1 .1589 2 .3000 1 .2250 1 .2255 1 2.15 3 .09 .02 5 .1148 3 .08135 .0502 8 .1458 2 .1143 3 3.55 3 .02 .03 6 .0259 11 .0664 8 .0619 7.0227 12 .0336 11 2.04 3 .11 .02 7 .0599 7 .0793 6 .0309 9 .0515 8 .05607 .85 3 .47 .01 8 .0508 8 .1033 4 03.09 9 .0503 9 .0546 9 1.87 3 .13 .029 .0879 5 .0682 7 .0658 6 .1068 4 .0896 4 .99 3 .40 .01 10 .0311 10.0240 12 .0019 12 .0605 6 .0371 10 3.33 3 .02 .03 11 .0446 9 .0498 10.1044 3 .0541 7 .0553 8 1.56 3 .20 .01 12 .0785 6 .1607 1 .1026 4 .047810 .0803 6 5.19 3 .00 .04

TABLE 10 Spearman's rho between countries for loss of control forpercent chosen and means Percent Means chosen Israel UK Canada KoreaIsrael .73* .73* .89* UK .68* .65* .46* Canada .66* .55* .59* Korea .85*.28* .45 *p < .05

TABLE 11 Top four photographs for premeditated assault for percentchosen and means by country Country Percent chosen Means Israel 4, 3, 5,1 4, 3, 5, 1 UK 12, 3, 4, 8 12, 4, 3, 8 Canada 4, 3, 11 = 12 4, 3, 11,12 Korea 4, 5, 3, 9 4, 5, 3, 9 Across Countries 4, 3, 5, 9 4, 5, 3, 9

TABLE 12 Percentages for photographs chosen for premeditated assault onall data 4 3 5 9 4 + 3 4 + 5 4 + 9 3 + 5 3 + 9 5 + 9 Israel 56.9 40.630.0 24.2 78.1 70.0 68.8 58.1 56.9 47.5 UK 26.7 28.9 17.8 20.0 51.1 42.240.0 37.8 40.0 26.7 BC 51.2 27.9 14.0 16.3 62.8 58.1 58.1 32.6 37.6 23.3Korea 56.8 36.4 41.7 12.9 84.1 77.3 67.4 56.8 56.1 54.5

TABLE 13 Means for photographs chosen for premeditated assault on alldata 4 3 5 9 4 + 3 4 + 5 4 + 9 3 + 5 3 + 9 5 + 9 Israel 0.2246 0.16040.1148 0.0879 0.3849 0.3394 0.3124 0.2482 0.2482 0.2027 UK 0.1589 0.13110.0813 0.0682 0.2900 0.2402 0.2271 0.2124 0.1993 0.1496 BC 0.3000 0.12160.0502 0.0658 0.4216 0.3502 0.3658 0.1719 0.1874 0.1160 Korea 0.22550.1418 0.1143 0.0896 0.3546 0.3708 0.3318 0.2754 0.2364 0.2525

Example 2 2.0 DIWS Analysis—Two Samples

Original sample had n of 585. From Israel there were 199 participants,from UK there were 50 participants, from Scotland Yard there were 84participants, from Canada there were 68 participants, from Korea 1 therewere 105 participants, and from Korea 2 there were 79 participants.Korea 1 refers to the first Korean data collection while Korea 2 refersto the second Korean data collection. Dropped all Scotland Yard data.

From remaining data, selected cases based on whether the participant hadwitnessed or experienced a physical assault. For Israel and Korea, aparticipant was selected if he or she had said yes to experiencing orwitnessing an assault on or off duty. For UK, a participant was selectedif he or she had said yes to being threatened with physical assault,being assaulted, or witnessing an assault. For Canada, a participant wasselected if he or she answered no to never seeing the facial expressionof someone just before they made a physical assault, no to notremembering someone's expression before an assault, and no to seeingsomeone's expression but not seeing it in the 12 pictures.

Selected sample had n of 385. From Israel there were 161 participants,from UK there were 46 participants, from Canada there were 46participants, from Korea 1 there were 65 participants, and from Korea 2there were 67 participants. All analyses were performed on this selectedsample.

Transformed data so that a total of one point was assigned to eachsubset for each participant: Loss of Control (LC), and PremeditatedAssault (PA)

Ran 24 chi-squares with country as the IV and photograph chosen as theDV. For LC, significant results for photos 2, 4, 6, 7, 10, and 11. (SeeTable 14). For PA, significant results for photos 4, 5, 10 and 12. (SeeTable 20).

Ran 24 one-way ANOVAS with country as IV and transformed data as the DV.For LC, significant results for photos 4, 6, 7, and 10. (See Table 15).For PA, significant results for photos 5, 10, and 12. (See Table 21).

Used percentage and mean data to run Spearman's rhos between countriesfor LC. For percentage data, significant among all country pairs. Formeans data, significant for all country pairs except for Korea 2 andCanada. (See Table 16). Used percentage and mean data to run Spearman'srhos between countries for PA. For percentage data, significant for allcountry pairs except for Korea 2 and UK, and Korea 2 and Canada. Formeans data, significant for all country pairs except for Korea 2 andCanada, and Korea 2 and Canada for means data. (See Table 22).

Identified top four photos chosen for LC (See Table 17) and PA (SeeTable 23) for percent chosen and means by country.

Examined top four photographs chosen for LC (See Tables 18 and 19) andPA (See Tables 24 and 25) by looking at all possible pairs. Data weretransformed so that participants were given one point for choosingeither of the photos in a pair, and zero points for not. Additionally,for the data in which one point was given for each subset, all possiblepairs from top four were summed.

TABLE 14 Percent chosen for each photo by country for loss of control(LC); Chi-square analyses for country on percent chosen for each photoAcross Israel UK BC Korea 1 Korea 2 Countries Chi-square Photo % forRanking % for Ranking % for Ranking % for Ranking % for Ranking % forRanking Asymp. Sig. ID LC for LC LC for LC LC for LC LC for LC LC for LCLC for LC x² df (2-sided) 1 3.1 9 0.0 10 4.7 6 1.5 10 4.5 10 2.9 11 2.904 .57 2 63.8 2 67.4 1 48.8 2 76.9 1 64..2 1 64.8 2 9.22 4 .06 3 4.4 72.2 7 4.7 6 6.2 7 4.5 10 4.5 7 1.01 4 .91 4 5.0 5 4.3 6 4.7 6 10.8 620.9 5 8.7 5 17.71 4 .00 5 3.8 8 0.0 10 0.0 11 6.2 7 7.5 7 3.9 8 6.71 4.15 6 79.4 1 67.4 1 51.2 1 75.4 2 58.2 2 70.3 1 19.55 4 .00 7 3.1 9 2.27 11.6 5 1.5 10 3.0 11 3.7 9 9.04 4 .06 8 40.6 4 34.8 4 27.9 3 32.3 435.8 4 36.2 4 3.11 4 .54 9 2.5 12 2.2 7 4.7 6 3.1 9 6.0 8 3.4 10 2.17 4.70 10 5.0 5 15.2 5 0.0 11 12.3 5 14.9 6 8.7 6 13.70 4 .01 11 49.4 350.0 3 23.3 4 66.2 3 50.7 3 49.6 3 19.10 4 .00 12 3.1 9 0.0 10 4.7 6 0.012 6.0 8 2.9 12 6.08 4 .19

TABLE 15 Means for each photo by country for loss of control (LC);One-way ANOVAs for country on each photo Across Israel UK BC Korea 1Korea 2 Countries Photo Means Ranking Means Ranking Means Ranking MeansRanking Means Ranking Means Ranking AVONA ID for LC for LC for LC for LCfor LC for LC for LC for LC for LC for LC for LC for LC F df Sig. η_(p)² 1 .0103 12 .0000 10 .0291 6 .0051 10 .0137 11 .0109 12 1.09 4, 376 .36.01 2 .2451 2 .3111 1 .2835 2 .2643 1 .2450 1 .2607 2 .80 4, 376 .53 .013 .0144 9 .0054 7 .0279 7 .0203 7 .0199 9 .0168 7 .46 4, 376 .77 .01 4.0176 6 .0435 6 .0123 8 .0382 6 .0697 5 .0328 5 2.85 4, 376 .02 .03 5.0124 10 .0000 11 .0000 11 .0203 7 .0249 7 .0130 9 1.70 4, 376 .15 .02 6.3083 1 .2893 2 .2912 1 .2540 2 .1978 2 .2754 1 3.03 4, 376 .02 .03 7.0145 8 .0030 8 .0519 5 .0051 10 .0100 12 .0149 8 2.24 4, 376 .06 .02 8.1404 4 .1157 4 .1149 4 .1118 4 .1343 4 .1286 4 .43 4, 376 .79 .01 9.0104 11 .0030 9 .0123 8 .0102 9 .0199 10 .0113 11 .53 4, 376 .72 .01 10.0207 5 .0526 5 .0000 11 .0406 5 .0498 6 .0307 6 2.42 4, 376 .05 .03 11.1829 3 .1737 3 .1170 3 .2200 3 .1940 3 .1828 3 1.66 4, 376 .16 .02 12.0156 7 .0000 12 .0123 8 .0000 12 .0211 8 .0116 10 1.01 4, 376 .40 .01

TABLE 16 Spearman's rho between countries for loss of control forpercent chosen and means Percent chosen Means Israel UK Canada Korea 1Korea 2 Israel .88* .61* .94 .88* UK .89* .72* .92* .83* Canada .61*.66* .56* .54* Korea 1 .83* .94* .54* .91* Korea 2 .82 .77* .20 .85* *p< .05

TABLE 17 Top four photographs for loss of control for percent chosen andmeans by country Percent Country chosen Means Israel 6, 2, 11, 8 6, 2,11, 8 UK 2 = 6, 11, 8 2, 6, 11, 8 Canada 6, 2, 8, 11 6, 2, 11, 8 Korea 12, 6, 11, 8 2, 6, 11, 8 Korea 2 2, 6, 11, 8 2, 6, 11, 8 Across 6, 2, 11,8 6, 2, 11, 8 Countries

TABLE 18 Percentages for photographs chosen for loss of control on alldata 6 2 11 8 6 + 2 6 + 11 6 + 8 2 + 11 2 + 8 11 + 8 Israel 79.4 63.849.4 40.6 90.0 86.3 87.5 81.9 80.6 77.5 UK 67.4 67.4 50.0 34.8 89.1 78.369.6 82.6 73.9 65.2 BC 51.2 48.8 23.3 27.9 74.4 62.8 55.8 58.1 60.5 41.9Korea 1 75.4 76.9 66.2 32.3 90.8 89.2 93.8 93.8 90.8 83.1 Korea 2 58.264.2 50.7 35.8 76.1 79.1 77.6 85.1 80.6 74.6

TABLE 19 Means for photographs chosen for loss of control on all data 62 11 8 6 + 2 6 + 11 6 + 8 2 + 11 2 + 8 11 + 8 Israel 0.3083 0.24510.1829 0.1404 0.5534 0.4913 0.4488 0.4281 0.3856 0.3234 UK 0.2893 0.31110.1737 0.1157 0.6004 0.4630 0.4050 0.4848 0.4267 0.2893 BC 0.2912 0.28350.1170 0.1149 0.5747 0.4081 0.4060 0.4005 0.3984 0.2319 Korea 1 0.25400.2643 0.2200 0.1118 0.5183 0.4749 0.3658 0.4852 0.3762 0.3328 Korea 20.1978 0.2450 0.0137 0.0211 0.4428 0.3918 0.3321 0.4391 0.3794 0.3284

TABLE 20 Percent chosen for each photo by country for premeditatedassault (PA); Chi-square analyses for country on percent chosen for eachphoto Across Israel UK BC Korea 1 Korea 2 Countries Chi-square Photo %for Ranking % for Ranking % for Ranking % for Ranking % for Ranking %for Ranking Asymp. Sig. ID PA for PA PA for PA PA for PA PA for PA PAfor PA PA for PA x² df (2-sided) 1 27.5 4 15.6 8 16.3 5 27.7 5 14.9 722.6 5 7.67 4 .11 2 3.1 12 4.4 12 4.7 11 6.2 11 6.0 12 4.5 12 1.47 4 .833 40.6 2 28.9 2 27.9 2 32.3 4 40.3 2 36.3 2 4.58 4 .33 4 56.9 1 26.7 351.2 1 69.2 1 44.8 1 52.6 1 22.20 4 .00 5 30.0 3 17.8 6 14.0 7 49.2 234.3 3 30.8 3 20.11 4 .00 6 6.9 11 11.1 9 11.6 8 1.5 12 11.9 9 7.9 116.81 4 .15 7 16.3 7 17.8 6 9.3 9 15.4 6 11.9 9 14.7 7 2.07 4 .72 8 12.58 24.4 4 7.0 10 10.8 8 14.9 7 13.4 8 6.88 4 .14 9 24.4 5 20.0 5 16.3 535.4 3 22.4 5 24.5 4 6.39 4 .17 10 7.5 10 6.7 11 2.3 12 9.2 10 23.9 410.0 10 18.87 4 .00 11 10.6 9 11.1 9 20.9 3 10.8 8 16.4 6 12.9 9 4.34 4.36 12 22.5 6 35.6 1 20.9 3 15.4 6 11.9 9 20.8 6 10.58 4 .03

TABLE 21 Means for each photo by country for premeditated assault (PA);One-way ANOVAs for country on each photo Across Israel UK BC Korea 1Korea 2 Countries Photo Means Ranking Means Ranking Means Ranking MeansRanking Means Ranking Means Ranking ANOVA ID for LC for PA for PA for PAfor PA for PA for PA for PA for PA for PA for PA for PA F df Sig. η_(p)² 1 .1014 4 .0533 9 .0735 5 .0622 8 .0839 5 .0839 5 1.19 4, 375 .32 .012 .0135 12 .0258 11 .0077 11 .0299 12 .0183 12 .0183 12 .52 4, 375 .72.01 3 .1604 2 .1311 3 .1216 2 .1443 2 .1418 2 .1418 2 .69 4, 375 .60 .014 .2246 1 .1589 2 .3000 1 .1940 1 .2255 1 .2255 1 2.10 4, 375 .08 .02 5.1148 3 .0813 5 .0502 8 .1194 3 .1143 3 .1143 3 3.38 4, 375 .01 .04 6.0259 11 .0664 8 .0619 7 .0398 11 .0336 11 .0336 11 2.10 4, 375 .08 .027 .0599 7 .0793 6 .0309 9 .0522 9 .0560 7 .0560 7 .64 4, 375 .64 .01 8.0508 8 .1033 4 .0309 9 .0647 7 .0546 9 .0546 9 1.70 4, 375 .15 .02 9.0879 5 .0682 7 .0658 6 .0945 4 .0896 4 .0896 4 .92 4, 375 .45 .01 10.0311 10 .0240 12 .0019 12 .0871 5 .0371 10 .0371 10 4.29 4, 375 .00 .0411 .0446 9 .0498 10 .1044 3 .0697 6 .0553 8 .0553 8 1.48 4, 375 .21 .0212 .0785 6 .1607 1 .1026 4 .0423 10 .0803 6 .0803 6 3.92 4, 375 .00 .04

TABLE 22 Spearman's rho between countries for loss of control forpercent chosen and means Percent chosen Means Israel UK Canada Korea 1Korea 2 Israel .73* .73* .95* .71* UK .68* .65* .64* .35 Canada .66*.55* .66* .49 Korea 1 .95* .59* .60* .69* Korea 2 .75* .34* .46 .76* *p< .05

TABLE 23 Top four photographs for loss of control for percent chosen andmeans by country Percent Country chosen Means Israel 4, 3, 5, 1 4, 3, 5,1 UK 12, 3, 4, 8 12, 4, 3, 8 Canada 4, 3, 11 = 12 4, 3, 11, 12 Korea 14, 5, 9, 3 4, 5, 9, 3 Korea 2 4, 3, 5, 10 4, 3, 5, 9 Across 4, 3, 5, 94, 3, 5, 9 Countries

TABLE 24 Percentages for photographs chosen for premeditated assault onall data 4 3 5 9 4 + 3 4 + 5 4 + 9 3 + 5 3 + 9 5 + 9 Israel 56.9 40.630.0 24.4 78.1 70.0 68.8 58.1 56.9 47.5 UK 26.7 28.9 17.8 20.0 51.1 42.240.0 37.8 40.0 26.7 BC 51.2 27.9 14.0 16.3 62.8 58.1 58.1 32.6 37.2 23.3Korea 1 69.2 32.3 49.2 35.4 89.2 87.7 80.0 60.0 58.5 61.5 Korea 2 52.636.3 30.8 24.5 79.1 67.2 55.2 53.7 53.7 47.8

TABLE 25 Means for photographs chosen for premeditated assault on alldata 4 3 5 9 4 + 3 4 + 5 4 + 9 3 + 5 3 + 9 5 + 9 Israel 0.2246 0.16040.1148 0.0879 0.3849 0.3394 0.3124 0.2752 0.2482 0.2027 UK 0.1589 0.13110.0813 0.0682 0.2900 0.2402 0.2271 0.2124 0.1993 0.1496 BC 0.3000 0.12160.0502 0.0658 0.4216 0.3502 0.3658 0.1719 0.1874 0.1160 Korea 1 0.25690.1145 0.1729 0.1194 0.3714 0.4298 0.3763 0.2874 0.2338 0.2923 Korea 20.1940 0.1443 0.1194 0.0945 0.3383 0.3134 0.2886 0.2637 0.2388 0.2139

Example 3 3.0 FACS Coding for DIWS

Table 26 itemizes the Facial Action Coding System (FACS) which indicatesa procedure to analyze human face expressions. This system may be usedto analyze and evaluate expressions in cooperation with embodiments ofthe present invention. Different evaluators may use different codes asindicated below.

TABLE 26 Expression FACS AU Muscle name Intensity level Premeditated 4Corrugator super- A-C Assault cilii, Depressor super- cilii 5 LevatorA-C palpebrae superioris 7 Orbicularis oculi, A-B pars palpebralis 23Orbicularis oris Top and/or bottom; A-C; may or may not be present 17Mentalis May or may not be present Loss of Control, 4 Corrugator super-C-E version 1 cilii, Depressor super- cilii 5 Levator C-E palpebraesuperioris 7 Orbicularis oculi, A-B: may or may pars palpebralis not bepresent 23 Orbicularis oris Top and/or bottom; A-D 26 Jaw drop Facereddening Loss of Control, 4 Corrugator super- D-E version 2 cilii,Depressor super- cilii 5 Levator C-E palpebrae superioris 7 Orbicularisoculi, C-E pars palpebralis 9 Levator labii C-E superioris alaquae nasi20 Risorius w/ platysma C-E Face reddening Jaw clench 10 Levator labiiMay or may not superioris be present 16 Depressor labii May or may notinferioris be present 23 Orbicidaris oris May or may not be present 21May or may not be present

Paul's Codes:

Premeditated: 4a/c+5a/c with or without 23t/b a/c, with or without 17,Loss of Control 6: 4c/e+5c/e+23t/b a/d+25+face redLoss of Control 2 4d/e+5c/e+7c/e+9c/e+20c/e+face red+jaw clenched withor without: 10, 23, 21

David and Hyi-Sung's Codes:

Premeditated 4A/B+5A/B+7A/B+23A/C (with/without 17)Loss of Control 2:4C/E+5C/E+7C/E+9C/E+10C/E+20C/E+23C/E+(BITE)+(with/without 16)+facecolorLoss of Control 11: 4C/E+5C/E+7C/E+23C/E+NO17 (with/without 9)Loss of Control 6: 4A/B+5E+7C/E+23C/E+26+face color

Thus, specific embodiments, methods and systems for identifying intentthrough facial expressions have been disclosed. It should be apparent,however, to those skilled in the art that many more modificationsbesides those already described are possible without departing from theinventive concepts herein. The inventive subject matter, therefore, isnot to be restricted except in the spirit of the disclosure herein.Moreover, in interpreting the specification and claims, all terms shouldbe interpreted in the broadest possible manner consistent with thecontext. In particular, the terms “comprises” and “comprising” should beinterpreted as referring to elements, components, or steps in anon-exclusive manner, indicating that the referenced elements,components, or steps may be present, or utilized, or combined with otherelements, components, or steps that are not expressly referenced.

1-20. (canceled)
 21. A method of creating and analyzing a plurality offacial expressions, comprising: identifying a subject person, utilizingthe subject person to create an image of a known target, removing atleast one distracter expression from the target image to form a revisedtarget image, reviewing the revised target image with at least one thirdparty participant to form a final target image; presenting, by acomputer, a user with multiple target images depicting a facialexpression, wherein the multiple target images include images ofdangerous intent and images of non-dangerous intent, and wherein themultiple target images include the final target image; receiving, by thecomputer, a response from the user, wherein the response indicateswhether or not the facial expression depicted in each target image ofthe multiple target images depicts a dangerous intent facial expression;determining, by the computer, whether the response is correct orincorrect; tracking, by the computer, a total number of correct andincorrect responses from the user; and displaying, by the computer, thetotal number of correct and incorrect responses to the user.
 22. Themethod of claim 21, wherein the subject person is a crime victim. 23.The method of claim 22, wherein the crime victim is an assault victim.24. The method of claim 21, wherein the known target is the criminal.25. The method of claim 24, wherein the criminal is an attacker.
 26. Themethod of claim 21, further comprising identifying at least one keyfeature in the final target image that depicts target intent.
 27. Themethod of claim 26, wherein the target intent comprises dangerousintent.
 28. The method of claim 21, further comprising comparing thefinal target image to at least one comparison image.
 29. The method ofclaim 21, wherein utilizing the subject person to create an image of aknown target includes digitizing the image.
 30. A method of creating andanalyzing a plurality of facial expressions, comprising: identifying asubject person, utilizing the subject person to create a target image ofa known target, digitizing the target image, removing at least onedistracter expression from the target image to transform the targetimage to a revised target image, reviewing the revised target image withat least one third party participant to transform the revised targetimage to a final target image; presenting, by the computer, a user withmultiple target images depicting a facial expression, wherein themultiple target images include images of dangerous intent and images ofnon-dangerous intent, and wherein the multiple target images include thefinal target image; receiving, by the computer, a response from theuser, wherein the response indicates whether or not the facialexpression depicted in each target image of the multiple target imagesdepicts a dangerous intent facial expression; determining, by thecomputer, whether the response is correct or incorrect; tracking, by thecomputer, a total number of correct and incorrect responses from theuser; and displaying, by the computer, the total number of correct andincorrect responses to the user.
 31. The method of claim 30, wherein thesubject person is a crime victim.
 32. The method of claim 31, whereinthe crime victim is an assault victim.
 33. The method of claim 30,wherein the known target is the criminal.
 34. The method of claim 33,wherein the criminal is an attacker.
 35. The method of claim 30, furthercomprising identifying at least one key feature in the final targetimage that depicts target intent.
 36. The method of claim 35, whereinthe target intent comprises dangerous intent.
 37. The method of claim30, further comprising comparing the final target image to at least onecomparison image.
 38. The method of claim 30, wherein utilizing thesubject person to create an image of a known target includes digitizingthe image.
 39. An executable software for implementing the method ofclaim 21, embodied on a non-transitory computer-readable medium, theexecutable software comprising: a set speed function, a pre-test phasefunction, an instruction phase function, a practice phase function, anda post-test phase function.
 40. A system comprising a computer forexecuting the executable software of claim
 39. 41. A method of analyzinga plurality of facial expressions, comprising: presenting, by acomputer, a user with multiple target images depicting a facialexpression, wherein the multiple target images include images ofdangerous intent and images of non-dangerous intent; receiving, by thecomputer, a response from the user, wherein the response indicateswhether or not the facial expression displayed in each target image ofthe multiple target images depicts a dangerous intent facial expression;determining, by the computer, whether the response is correct orincorrect; tracking, by the computer, a total number of correct andincorrect responses from the user; and displaying, by the computer, thetotal number of correct and incorrect responses to the user.
 42. Themethod of claim 41, further comprising: providing the user withinstructions for identifying dangerous intent facial expressions,wherein the instructions comprise a depiction of dangerous intent facialexpressions, and wherein the instructions contrast the dangerous intentfacial expression depictions with a depiction of distracter facialexpressions.